کمینه‌سازی تابع هدف چندمتغره بااستفاده از الگوریتم ژنتیک بهبودیافته در کنترل فعال نوسان‌های سازه

نوع مقاله : پژوهشی

نویسندگان

1 دانشگاه آزاد اسلامی واحد مشهد

2 دانشگاه آزاد اسلامی مشهد

چکیده

  مقاله پیش‌رو فرایند نوینی در کنترل فعال سازه­ها دربرابر بار دینامیکی ناشی از زلزله، برمبنای روش­های جستجوی عددی هوشمند ارائه می­دهد. در اینجا، با متصل کردن عملگر دینامیکی به درجه­ های آزادی سازه و استفاده از روش الگوریتم ژنتیک پیشنهادی برای یافتن نیروهای کنترلی مناسب در هرگام زمانی باتوجه به وضعیت جابه­جایی گره­ها، تغییرمکان سازه کنترل و کمینه می­شود. جابه­جایی­های گره­ای سازه در هرگام زمانی با حل معادله­های تعادل دینامیکی به‌دست می­آیند. با ارزیابی این جابه­ جایی­ ها و استفاده از تابع هزینۀ پیشنهادی، نیروهای عملگرها با فرایند تخمین- تصحیح الگوریتم ژنتیک تعیین می­شوند. هم‌چنین، به‌دلیل ماهیت تخمین- تصحیح روش الگوریتم ژنتیک، اثر تأخیر زمانی در کنترل نوسان­های سازه درنظر گرفته می­شود. برای نشان دادن کارایی روش پیشنهادی در کنترل نوسان­های سازه، سه نمونه عددی به‌کار می­رود و نتایج با روش سامانگر درجه­ دوی خطی (LQR) مقایسه می­گردند. بر این اساس، روش پیشنهادی توانایی مناسبی برای کنترل نوسان­های سازه دارد.

کلیدواژه‌ها

عنوان مقاله [English]

Minimizing Multivariate Objective Function Using Improved Genetic Algorithm in Active Control of Oscillation of Structures

نویسندگان [English]

  • Ali Banaei 1
  • javad alamatian 2
1 Islamic Azad Univ. of Mashhad
2 Islamic Azad Univ. of Mashhad
چکیده [English]

This paper aims to design a special active control system based on the proposed genetic algorithm for active control of structures. In this trend, by connecting the actuator to the structure’s freedom degrees and using the proposed method to find the proper control forces, the structure’s movement is controlled and minimized. The nodal displacements are calculated by solving the dynamic equations of motion at each time step. By evaluating these responsese and utilizing the proposed cost function, the proper actuator’s forces are determined during the prediction-correction process of the genetic algorithm. Moreover, due to the nature of the prediction-correction of the genetic algorithm method, the effect of time delay on the control scheme is mentioned. To illustrate the effectiveness of the proposed method for controlling the oscillations of the structure, three numerical examples are solved and the results are compared with the linear differential equation (LQR) method. Accordingly, the proposed method has a very good ability to control the oscillations of the structure.
 

کلیدواژه‌ها [English]

  • Optimization
  • Structures Active Control
  • Genetic algorithm
  • Numerical Analysis

مراجع

1. Tzou, H., Lee, H.-J. and Arnold, S., "Smart Materials, Precision Sensors/actuators, Smart Structures, and Structronic Systems", Mechanics of Advanced Materials and Structures, Vol. 11, Pp. 367-393, (2004).
2. Yao, J. T., "Concept of Structural Control", Journal of the Structural Division, Vol. 98, Pp. 1567-1574, (1972).
3. Yang, J. N., "Instantaneous Optimal Control for Linear, Nonlinear and Hysteretic Structures-stable Controllers", (1991).
4. Jabbari, F., Schmitendorf, W., and Yang, J., "H∞ Control for Seismic-excited Buildings with Acceleration Feedback", Journal of Engineering Mechanics, Vol. 121, Pp. 994-1002, (1995).
5. Yang, J. and Soh, C. K., "Structural Optimization by Genetic Algorithms with Tournament Selection", Journal of Computing in Civil Engineering, Vol. 11, Pp. 195-200, (1997).
6. Holland, J. H., "Outline for a Logical Theory of Adaptive Systems", Journal of the ACM (JACM), Vol. 9, Pp. 297-314, (1962).
7. 2esley Publishing Company, R eading, MA, Vol. 1, P. 9, (1989).
8. Houck, C. R., Joines, J. and Kay, M. G., "A Genetic Algorithm for Function Optimization: A Matlab Implementation", NCSU-IE TR, Vol. 95, (1995).
9. Safizadeh, M. R. and Darus, I. Z., "Optimal Location of Sensor for Active Vibration Control of Flexible Square Plate", in Information Sciences Signal Processing and their Applications (ISSPA), 10th International Conference on, Pp. 393-396, (2010).
10. Cha, Y.-J., Agrawal, A. K., Kim, Y. and Raich, A. M., "Multi-objective Genetic Algorithms for Cost-effective Distributions of Actuators and Sensors in Large Structures", Expert Systems with Applications, Vol. 39, Pp. 7822-7833, (2012).
11. Cha, Y. J., Raich, A., Barroso, L. and Agrawal, A., "Optimal Placement of Active Control Devices and Sensors in Frame Structures Using Multi‐Objective Genetic Algorithms", Structural Control and Health Monitoring, Vol. 20, Pp. 16-44, (2013).
12. Hale, J. and Daraji, A., "Optimal Placement of Sensors and Actuators for Active Vibration Reduction of a Flexible Structure Using a Genetic Algorithm Based on Modified Hinfinity", Journal of Physics: Conference Series, P. 012036, (2012).
13. Abbasi, M. and Markazi, A., "Optimal Assignment of Seismic Vibration Control Actuators Using Genetic Algorithm", International Journal of Civil Engineering, Pp. 24-31, (2014).
14. Zhai, J., Zhao, G. and Shang, L., "Integrated Design Optimization of Structure and Vibration Control with Piezoelectric Curved Shell Actuators", Journal of Intelligent Material Systems and Structures, P. 1045389X16641203, (2016).
15. Zhu, K., Gu, C., Qiu, J., Liu, W., Fang, C. and Li, B., "Determining the Optimal Placement of Sensors on a Concrete Arch Dam Using a Quantum Genetic Algorithm", Journal of Sensors, Vol. 2016, (2016).
16. Kumar, M. S. and Vijayarangan, S., "Design of LQR Controller for Active Suspension System", (2006).
17. Clough, R. and Penzien, J., "Dynamics of Structures", McGraw Hill, New York, (1993).
18. Miyamoto, K., Sato, D. and She, J., "A New Performance Index of LQR for Combination of Passive Base Isolation and Active Structural Control", Engineering Structures, Vol. 157, Pp. 280-299, (2018).
19. Elumalai, V. K. and Subramanian, R. G., "A New Algebraic LQR Weight Selection Algorithm for Tracking Control of 2 DoF Torsion System", Archives of Electrical Engineering, Vol. 66, Pp. 55-75, (2017).
20. Oliveira, F., Morais, P. and Suleman, A., "A Comparative Study of Semi-active Control Strategies for Base Isolated Buildings", Earthquake Engineering and Engineering Vibration, Vol. 14, Pp. 487-502, (2015).
21. Tairidis, G., Foutsitzi, G. and Stavroulakis, G. E., "A Multi-layer Piezocomposite Model and Application on Controlled Smart Structures", Advances in Mechanics of Materials and Structural Analysis, ed: Springer, Pp. 3.65-385, (2018).
22. Newmark, N. M., "A Method of Computation for Structural Dynamics", Journal of the engineering mechanics division, Vol. 85, Pp. 67-94, (1959).
23. Goudreau G. L., and Taylor, R. L., "Evaluation of Numerical Integration Methods in Elastodynamics", Computer Methods in Applied Mechanics and Engineering, Vol. 2, Pp. 69-97, (1973).
24. Holland, J., "Book: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology", Control, and Artificial Intelligence, (1975).
25. Forrest, S., "Genetic Algorithms- Principles of Natural Selection Applied to Computation", Science, Vol. 261, Pp. 872-878, (1993).
26. Lobo, F., Lima, C. F. and Michalewicz, Z., Parameter Setting in Evolutionary Algorithms, Vol. 54: Springer Science & Business Media, (2007)
ارسال نظر در مورد این مقاله
CAPTCHA Image

فایل ها

هم رسانی

ارجاع به این مقاله

آمار